phoenix-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "James Taylor (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (PHOENIX-2288) Phoenix-Spark: PDecimal precision and scale aren't carried through to Spark DataFrame
Date Fri, 13 Nov 2015 17:39:10 GMT

    [ https://issues.apache.org/jira/browse/PHOENIX-2288?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15004350#comment-15004350
] 

James Taylor commented on PHOENIX-2288:
---------------------------------------

+1. No need to move it to SchemaUtil - just wanted to avoid duplicating the code. Thanks,
[~jmahonin]. Please commit to 4.x and master branches.

> Phoenix-Spark: PDecimal precision and scale aren't carried through to Spark DataFrame
> -------------------------------------------------------------------------------------
>
>                 Key: PHOENIX-2288
>                 URL: https://issues.apache.org/jira/browse/PHOENIX-2288
>             Project: Phoenix
>          Issue Type: Bug
>    Affects Versions: 4.5.2
>            Reporter: Josh Mahonin
>         Attachments: PHOENIX-2288-v2.patch, PHOENIX-2288-v3.patch, PHOENIX-2288.patch
>
>
> When loading a Spark dataframe from a Phoenix table with a 'DECIMAL' type, the underlying
precision and scale aren't carried forward to Spark.
> The Spark catalyst schema converter should load these from the underlying column. These
appear to be exposed in the ResultSetMetaData, but if there was a way to expose these somehow
through ColumnInfo, it would be cleaner.
> I'm not sure if Pig has the same issues or not, but I suspect it may.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

Mime
View raw message